Moodle-based data mining potentials of MOOC systems at the University of Szeged
In today's world virtual online educational platforms emerge literally on daily bases and many offer MOOC-based courses. With the appearance of MOOC, educational platforms have gained an additional boost, a new aspect in their evolutionary process, which has opened a new field of research thank...
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| Dokumentumtípus: | Könyv része |
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IEEE
New York (NY)
2017
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| Sorozat: | 2017 40TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO)
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| Tárgyszavak: | |
| doi: | 10.23919/MIPRO.2017.7973523 |
| mtmt: | 31559478 |
| Online Access: | http://publicatio.bibl.u-szeged.hu/23817 |
| Tartalmi kivonat: | In today's world virtual online educational platforms emerge literally on daily bases and many offer MOOC-based courses. With the appearance of MOOC, educational platforms have gained an additional boost, a new aspect in their evolutionary process, which has opened a new field of research thanking to the extraction of logging information within the frames of data mining. It has become clear that educators will be able to tailor their courses by merging the two previously mentioned fields and by carrying out MOOC-based data mining, targeting pedagogical aspects. This field of research seems promising and important, thus a faculty at the University of Szeged has created its own MOOC educational platform which has been set to facilitate data mining by implementing a wide range of logging algorithms. The data would be processed through a complex Artificial Intelligence program, which, in the short term, could reveal new and exciting pedagogical findings, while in the long run, the supervisors could put together a platform that would help and notify educators about relevant information. It would become possible to create adaptive educational materials, as well. This work aims at clarifying how such platforms function and what the steps of data collection and evaluation are. |
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| Terjedelem/Fizikai jellemzők: | 6 755-760 |
| ISBN: | 9789532330922 |